Airborne LiDAR: A New Source of Traffic Flow Data

Light Detection and Ranging (LiDAR) (or airborne laser scanning) systems became a dominant player in high-precision spatial data acquisition to efficiently create Digital Elevation Model/Digital Surface Model (DEM/DSM) in the late 90's. With increasing point density, new systems are now able to support object extraction, such as extracting buildings and roads, from LiDAR data. The novel concept of this project was to use LiDAR data for traffic flow estimates. In a sense, extracting vehicles over transportation corridors represents the next step in complexity by adding the temporal component to the LiDAR data feature extraction process. The facts are that vehicles are moving at highway speeds and the scanning acquisition mode of the LiDAR certainly poses a serious challenge for the data extraction process. The Ohio State University (OSU) developed method and its implementation, the I_FLOW program, have demonstrated that LiDAR data contain valuable information to support vehicle extraction, including vehicle grouping and localizations. The classification performance showed strong evidence that the major vehicle categories can be efficiently separated. The I_FLOW program is ready for deployment.

Language

  • English

Media Info

  • Media Type: Print
  • Features: Appendices; Bibliography; Figures; Photos; Tables;
  • Pagination: 79p

Subject/Index Terms

Filing Info

  • Accession Number: 01019632
  • Record Type: Publication
  • Report/Paper Numbers: FHWA/OH-2005/14
  • Contract Numbers: 134145
  • Files: NTL, TRIS, ATRI, USDOT, STATEDOT
  • Created Date: Jan 13 2006 9:38AM